In making a diagnosis, it is often useful to have the patient's cooperation. This is particularly true in the diagnosis of disease involving sensory pathways to the brain. For example, a straightforward way to assess a patient's hearing is to simply ask the patient whether he can hear particular tones having various frequencies and amplitudes.
In many cases, one takes for granted that a patient will be able to answer such questions. However, in some cases, a patient cannot communicate his perception. This occurs most frequently when the patient is an infant, or when the patient is unconscious. In a veterinary setting, it is rare to encounter a patient that can accurately communicate perception at all.
One approach to evaluating an infant's hearing is to make a sound and to then measure an evoked response associated with that sound. This evoked response is typically an electrophysiologic signal generated in response to the sound and traveling between the inner ear and the brain along various neural pathways, one of which includes the auditory brainstem. This signal is thus referred to as the “auditory brainstem-response,” hereafter referred to as the “ABR.”
The ABR is typically only a small component of any measured electrophysiologic signal. In most cases, a noise component arising from other, predominantly myogenic, activity within the patient dwarfs the ABR. The amplitude of the ABR typically ranges from approximately 1 microvolt, for easily audible sounds, to as low as 20 nanovolts, for sounds at the threshold of normal hearing. The noise amplitude present in a measured electrophysiologic signal, however, is typically much larger. Typical noise levels range from between 2 microvolts to as much as 2 millivolts. The resulting signal-to-noise ratio is thus between −6 dB and 100 dB
One approach to increasing the signal-to-noise ratio is to exploit differences between the additive properties of the ABR and that of the background noise. This typically includes applying a repetitive auditory stimulus (a series of clicks, for example) and sampling the electrophysiologic signal following each such stimulus. The resulting samples are then averaged. The ABR component of the samples add linearly, whereas the background electrophysiologic noise, being essentially random, does not. As a result, the effect of noise tends to diminish with the number of samples. The number of samples required to reach a specified signal-to-noise level depends on the noise level present in the samples. In principle, therefore, one can achieve a specified signal-to-noise ratio either with a small number of relatively quiet samples or with a large number of relatively noisy samples.
In practice, signal averaging techniques such as that described above are unlikely to work when the signal-to-noise ratio is worse than −48 dB. Since a minimally acceptable 5% confidence level requires a signal-to-noise ratio of at least −4 dB, this signal-averaging approach is prone to inaccuracy.
Signal averaging methods as described above perform best when the background noise is relatively constant. For example, the steady drone of an air-conditioner can readily be separated from a signal of interest. Such background noise is referred to as “stationary” noise.
The noise component of an electrophysiologic signal is often non-stationary. For example, after a few minutes of taking measurements, an infant may begin to stir, thereby momentarily increasing the background electrophysiologic noise level. The infant might then return to a deep sleep, thereby reducing the background electrophysiologic noise level.
The non-stationary nature of the noise component poses a dilemma for a clinician attempting to measure the ABR. For example, if the infant begins to stir, the clinician might suspend taking measurements to avoid contaminating data already collected with noisy data. This might prove to be a good decision if the infant were to fall back into a deep sleep, since one could then acquire additional quiet samples. However, even noisy samples can improve signal-to-noise ratio, provided that there are enough of them available. Hence, this might also prove to be a poor decision if the infant were to continue stirring. In such a case, it would have been better to have acquired the additional, albeit noisy samples. Because the behavior of an infant is, to a great extent, unpredictable, the clinician occasionally makes an incorrect guess, thereby either wasting time or needlessly corrupting acquired data.